The present invention is directed to the use of computational and other experimental data in the design of new pharmaceuticals, and in predicting the metabolism profiles thereof. Computational and other information is used to further understand drug metabolism and toxicology, particularly in relation to monooxygenase enzymes, such as those of the cytochrome P450 system, that are involved in drug metabolism. Information derived according to the practice of the invention is useful in predicting the clearance or half-life of drugs, the propensity for drug interactions, and the nature and toxicity of byproducts resulting from their metabolism. The invention provides novel and powerful new approaches to drug design.
The opportunity to improve the efficiency of the discovery phase of drug discovery is widely recognized in the pharmaceutical industry. Combinatorial chemistry and parallel synthesis methodologies, genomics, robotics, miniaturization, high-throughput screening and information technology together have stimulated an explosion of potential new lead compounds. However, limited expertise and resources are available to move a compound from xe2x80x9ccandidatexe2x80x9d to xe2x80x9cleadxe2x80x9d. This is partially because the development of new technologies to address the later stages of the lead optimization process have not kept pace with the combinatorial technologies developed for synthesis and screening. As a result, there is a bottleneck in the drug discovery process that begins with lead optimization and extends all the way to the selection of clinical development candidates.
A primary consideration in the area of lead development is a compound""s metabolic fate. It would be of great value to the pharmaceutical industry if the discovery of such lead substances could be accelerated by design approaches that minimize reliance on screening synthesized compounds, but instead take advantage of quantifiable chemical or biochemical properties of a molecule in order to predict its metabolic characteristics. Predictive models can not only help alleviate the bottleneck in lead optimization but to facilitate the design and selection of drug candidates with not just adequate but with optimal absorption, distribution, metabolism and excretion/pharmacokinetic (ADME/PK) profiles for progression to the later, more costly stages of the drug discovery/development process. Compounds thus selected will not only have a greater chance of development success but will ultimately lead to better medicines.
In connection with the design of optimized pharmaceutical compounds, one particular area of interest involves a class of enzymes known as heme-containing monooxygenases, mixed function oxygenases, or alternatively cytochrome P-450s. These enzymes, which are abundant in the liver, act on a very broad range of substrate compounds, which is a trait very unusual for enzymes. These enzymes react with molecular oxygen such that one of the oxygen atoms is reduced to water, and the other is inserted into a substrate organic compound. This metabolic reaction may also be referred to as a hydroxylation reaction.
The cytochrome P450 (CYP) enzymes comprise a superfamily of heme-containing enzymes that consists of more than 700 individual isoforms, and are found in plant, bacterial and mammalian species (Nelson et al. (1996) Pharmacogenetics 6, 1-42). These enzymes function mainly as monooxygenases (Wislocki et al. (1980) in Enzymatic Basis of Detoxification (Jakoby, W. B., Ed.) pp 135-82, Academic, New York). In mammals, they are responsible for the metabolism of certain endogenous as well as exogenous compounds (Gonzalez, F. J. (1992) Trends Pharmacol. Sci. 13, 346-52). The catalytic cycle for aliphatic hydroxylation by mammalian CYP is described here briefly and shown in FIG. 1. Substrate binding changes the equilibrium of the heme iron from the low spin to the high spin state (step 1). This change lowers the reduction potential for the iron and facilitates electron transfer from NADPH via another enzyme, cytochrome P450 reductase (step 2). Molecular oxygen binds and is reduced by one electron as iron changes from the ferrous to the ferric state (steps 3 and 4). A second electron reduction of oxygen occurs and a peroxy intermediate is formed (step 5). The peroxy species undergoes heterolytic cleavage: one atom of oxygen leaves as a hydroxyl anion and the other forms a reactive oxygen species which is coordinated with the iron (step 6). Oxygen is transferred to the substrate (steps 7 and 8) and product dissociates from the enzyme (step 9). The first three steps of the cycle have been characterized spectroscopically. The next three steps occur rapidly, and have proven difficult to measure. At least two mechanisms have been proposed for the step(s) of oxygen transfer (depicted as steps 7 and 8 in FIG. 1), and are described briefly below.
The consensus mechanism for oxygen transfer is a nonconcerted reaction. In this context, nonconcerted implies that there are two distinct steps and that each step has its own transition state. There is evidence that step 7 (FIG. 1) is abstraction of a hydrogen atom from the substrate by the reactive oxygen, which yields a carbon-based radical and an iron bound hydroxyl radical (White et al. (1980) Ann. Rev. of Biochem. 49, 315-56). The next step (step 8 in FIG. 1) is rapid recombination of the two radical species, the xe2x80x9coxygen reboundxe2x80x9d step. The magnitudes of isotope effects (Groves et al. (1978) Biochemical and Biophysical Research Communications 81, 154-60; and Hjelmeland et al. (1977) Biochem. Biophys. Res. Commun. 76, 541-9), loss of stereoselectivity (Groves et al., Ibid; and White et al. (1986) J. Am. Chem. Soc. 108, 6024-31), and evidence for rearrangement of the radical-like product of the first step (Groves et al. (1984) J. Am. Chem. Soc. 106, 2177-81) in various CYP-mediated reactions support the case for the oxygen rebound mechanism.
Suitable substrates for CYP include steroids, prostaglandins, fatty acids, and exogenous drugs, pesticides and other toxic environmental contaminants including many carcinogens. Hydroxylation reactions are often the first step in the metabolism of foreign substances leading, for example, to the inactivation of administered pharmaceuticals. Depending upon the mechanism of action of a drug, and its toxicological profile, it may be desirable to accelerate or delay its breakdown once it enters the body. Additionally other potential pharmaceuticals may be too toxic to administer, but appropriate structural modifications thereof may lead, for example, to structures that are decomposed to different, and less toxic, metabolites.
For example, metabolism of phenylacetonitrile at the benzylic position (FIG. 2, see arrow) causes the release of the toxic metabolite cyanide, whereas aromatic oxidation leads to a less toxic product (Silver et al. (1982) Drug Metab. Dispos. 10, 495-8). The metabolism of benzo(12)pyrene (Franchetti et al. (1995) J. Med. Chem. 38, 3829-37) by CYP and epoxide hydrolase yields several metabolites including the extremely carcinogenic compound 7(R),8(S)-dihydrodiol 9(S),10(R)-epoxide. These are examples where regioselectivity and stereoselectivity are important determinants of toxicity.
In addition, potential drug interactions can be caused by differences in metabolism of multiple drugs by a single CYP isoform, as well as the induction or inhibition of individual CYP isoforms by drugs. Polymorphic enzyme expression among individuals may cause unusual patterns of drug metabolism, which can lead to unwanted side effects.
As aforementioned, there is a tremendous need to enhance presently available methods for drug design to minimize dependence on the testing of randomly modified structures. But while progress has been made in the area of basic research, the field of predictive metabolism is not widespread in industry at this time. The two main determinants of enzymatic reactions are the steric and electronic characteristics of the enzyme and the substrate. Various electronic models have been developed that use computational (Grogan et al. (1992) Chem. Res. Toxicol. 5, 548-52; Korzekwa et al. (1990) J. Am. Chem. Soc. 112, 7042-6; and Yin et al. (1995) Proc. Natl. Acad. Sci. USA 92, 11076-80) and chemical (Karki et al. (1995) J. Am. Chem. Soc. 117, 3657-64; and Manchester et al. (1997) J. Am. Chem. Soc. 119, 5069-70) approaches for the successful prediction of relative reaction rates and isotope effect profiles for some classes of small compounds which are metabolized by CYP. The small sizes of the compounds reduce, or nearly eliminate, the steric contribution to the outcome of metabolism.
In some cases steric factors are the main determinants of CYP-substrate interactions (Jones et al. (1995) Biochemistry 34, 6956-61). Computational methods, which include molecular dynamics and molecular modeling, are currently employed to probe the interactions between the substrate and the enzyme (Jones et al. (1993) J. Am. Chem. Soc. 115, 381-7). These methods rely on the crystal structure of a CYP protein, but only a few crystal structures exist for four (soluble) bacterial CYP isoforms (Ravichandran et al. (1993) Science 261, 731-6; Poulos et al. (1987) Journal of Molecular Biology 195, 687-700; Hasemann et al. (1994) Journal of Molecular Biology 236, 1169-85; and Cupp-Vickery et al. (1995) Structural Biology 2, 144-53). Crystal structures for the (membrane bound) mammalian isoforms are not available. Although there is low sequence homology between bacterial and mammalian CYPs, current data suggests that some degree of tertiary structure is conserved (Korzekwa et al. (1993) Pharmacogenetics 3, 1-18). With the bacterial isoforms as a template, homology modeling techniques have been used to generate structural models of the mammalian isoforms (Hasemann et al. (1995) Structure 3, 41-62). The structural models have proven successful in locating residues near the active sites of mammalian CYPs (Szklarz et al. (1995) Biochemistry 34, 14312-22). The results have initiated site-directed mutagenesis studies, which have provided additional information about the structural details of the active site (Kobayashi et al. (1998) Biochemistry 37, 6679-88). This additional information has in turn been used to refine the homology models. The challenge remains to find a model that combines structural and electronic information for the prediction of the outcome of mammalian CYP-mediated reactions.
The present invention is directed to the use of computational models, in concert with other experimental data, to identify probable therapeutic compounds having improved therapeutic or toxicological profiles. CYP enzymes are amenable to the development of electronically based or quantum chemical predictive computational models for two reasons. 1) Many isoforms display low substrate specificity due to weak enzyme-substrate interactions. 2) The catalytic step of the enzyme family is thought to be the heterolytic cleavage of molecular oxygen (step 6 in FIG. 1). Therefore, for substrates that have weak interactions with the binding site of the enzyme, it is possible that the electronic features of the active oxygen and the inherent reactivities of various functional groups on a single molecule will dictate relative rates of metabolism.
The invention thus provides a system whereby computational and experimental data can be combined to define a unified model of drug reactivity. The methods thus provide for computational models for predicting rates and regiospecificity of drug metabolism. Although the approach is described in reference to properties resultant from interaction with monooxygenase enzymes such as CYP, it will be appreciated that the general principles are applicable in a wide variety of contexts.
The present invention is directed to methods that use experimental data, and also quantum mechanical (including electronic configuration) data, to parameterize the predicted reactivities of various substances, and their metabolites and precursors, upon interaction with an enzyme. The methods are most applicable for enzymes with broad substrate specificity (or low substrate selectivity). Examples of such enzymes include monooxygenases, glucoronyl transferases, and glutathione transferases.
Sample substances for which parameterization is desirable include various drug compounds or pharmaceutically active agents as well as any molecule introduced (such as by ingestion or inhalation) into a living organism. Upon such introduction, the substances may undergo reactions with various enzymes, including the monooxygenase cytochrome P-450 (CYP). Substrate reactions with CYP type enzymes, include for example, resultant hydrogen atom abstraction, aromatic oxidation, and metabolism at carbonyl groups or at heteroatoms.
Thus one aspect of the invention involves analysis of regioselectivities of various possible enzymatic reactions, and of the underlying chemical reactions, to identify structural features in pharmaceuticals that provide for advantages in non-adverse metabolism or bioactivation to toxic metabolites, half-life and dosing. As surprisingly described below, the regioselectivity of the underlying chemical reactions is often of greatest importance in such determinations.
In an uncatalyzed reaction, the regioselectivity of the reaction reflects the energetic differences for reaction of the various positions of the involved molecules. In an enzyme catalyzed reaction, however, the substrate compound is often bound to the enzyme in a very specific fashion, thereby changing the regioselectivity. The separation of reactivity differences intrinsic to the substrate from those attributed to steric interactions imposed by the enzyme is generally very difficult. Stated differently, it would generally be difficult to predict the effect of a structural modification of a target compound upon its metabolism by enzymes, given that the molecular mechanisms of its metabolism involve an intimate combination of effects contributed by the metabolizing enzymes and the compounds themselves.
According to the practice of the present invention however, it has been determined that, with respect to metabolism of various compounds (including potential pharmaceutical substances), large amounts of predictive information pertaining to optimized metabolism by enzymes with broad substrate specificity are, in fact, directly derivable from the regioselectivity of underlying electronic structure of the reactants. As such, the information may be derived without requiring reference to the enzymes. This greatly facilitates computational analysis of optimized structural features in newly designed therapeutics.
Without being limited as to theory, it is believed that certain enzymes, such as CYP, have evolved to metabolize a wide range of substances not otherwise readily metabolized or detoxified. As a result, and in order to provide a broad range of response, the normal high selectivity of enzymes for particular substances, and the steric requirements normally found at enzyme active sites, have been lessened, thus substantially enhancing the value of computational information that may be derived solely by reference to the electronic configuration of the metabolized substrates.
Although the above concepts are primarily described herein with respect to human pharmaceuticals and CYP, the methods of the invention are also applicable to any enzyme with broad substrate specificity for the design of industrial or agricultural chemicals, and the like, where interest is focused not on optimizing dose or pharmacodynamics, but rather avoiding metabolism (bioactivation or inactivation) of substances that may come in contact with the human body (such as pesticides or pharmaceutical agents) where it is intended to avoid undesirable metabolism.